Automated Vetting and Protocolling of MRI Examinations (AutoProMpt)
Automated Vetting and Protocoling of MRI Examination Referrals Using Explainable Large Language Models (LLM) With Retrieval Augmented Generation (RAG) (XLLM) Techniques- A Multi-stage Study
Background Vetting and assigning of protocols to MRI scan requests are usually carried out by radiologists and radiographers. This way is both time-consuming and prone to error. Recent improvements in Artificial Intelligence (Al) like Large Language Models (LLMs) are better at processing human language. It could be used to improve tasks like image reporting and assigning protocols in radiology.
Approach Firstly, I will find out about the delays in the way this is currently done. I will use a survey to find out the perceptions of radiologists to both the current process and the proposed Al intervention.
I will then use an LLM to undertake referral and protocol tasks. I will compare its performance to the performance of clinical specialists and established guidelines.
I will present the explanation reports to radiologists and ask them if they can be understood and whether they can be trusted as clinically reliable.
Impact My research could help reduce the workload and time radiologists spend dealing with scan requests. The findings will help design future research to consider application in real clinical settings.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Estimated)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: Edozie Iweka, MSc (Dist)
- Phone Number: +441225386989
- Email: eoi29@bath.ac.uk
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Genders Eligible for Study
Sampling Method
Study Population
This study is multi-stage multi-center research involving retrospective MRI referral data of patients and collected across three NHS Foundation Trusts in the United Kingdom.
Description
Inclusion Criteria:
- Patients who have had MRI examinations in the study sites
- Patients with MRI referrals submitted through electronic referral systems
- Patients whose MRI referrals were vetted and protocolled prior to examination
Exclusion Criteria:
- Patients who have had other imaging examination outside the MRI
- Patients with paper referrals scanned in electronic referral systems
- Patients for MRI examinations without vetting and protocolling
Study Plan
How is the study designed?
Design Details
- Observational Models: COHORT
- Time Perspectives: RETROSPECTIVE
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Group
Adult Patients undergoing MRI examinations |
No Intervention as this is an experiment on retrospective collected referral data |
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Accuracy
Time Frame: Through study completion, an average of 2 years
|
Accuracy of pretrained LLMs+RAG in automating vetting and protocolling of MRI examination referrals. |
Through study completion, an average of 2 years
|
Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Clinical Usefulness
Time Frame: Through study completion, an average of 2 years
|
Clinical usefulness of explainability reports on the performance of pretrained LLMs+RAG in automating vetting and protocolling of MRI examination referrals. |
Through study completion, an average of 2 years
|
Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Study record dates
Study Major Dates
Study Start (Estimated)
Study Start
Primary Completion (Estimated)
Primary Completion
Study Completion (Estimated)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 18376
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
No patient identifiable data will be collected from this study. All collected data will be held by the sponsor institution, University of Bath as per local research data policy.
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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